Author : Jun Ma
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Book Synopsis Modified Fisher Scoring Algorithms Using Jacobi Or Gauss-Seidel Subiterations by : Jun Ma
Download or read book Modified Fisher Scoring Algorithms Using Jacobi Or Gauss-Seidel Subiterations written by Jun Ma and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a parameter estimation problem with large numbers of unknown parameters, traditional algorithms such as fisher scoring and Newton-Raphson become impractical. A typical case is solution by discretization of linear inverse problems; an example is medical image reconstruction from projections. This article introduces a modification to the Fisher scoring method. Instead of solving the linear system of equations of each Fisher scoring iteration exactly, the solution of these equations is approximated by using the Jacobi or Gauss-Seidel scheme. Simulation studies show that these modified algorithms, especially the one with Gauss-Seidel scheme, exhibit much faster convergence than competitors such as the EM algorithm.
